Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r93290858
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -592,6 +629,59 @@ object GeneralizedLinearRegression extends
DefaultParamsReadable[GeneralizedLine
}
/**
+ * Tweedie exponential family distribution.
+ * The default link for the Tweedie family is the log link.
+ */
+ private[regression] object Tweedie extends Family("tweedie") {
+
+ val defaultLink: Link = Log
+
+ var variancePower: Double = 1.5
+
+ override def initialize(y: Double, weight: Double): Double = {
+ if (variancePower > 1.0 && variancePower < 2.0) {
+ require(y >= 0.0, "The response variable of the specified Tweedie
distribution " +
+ s"should be non-negative, but got $y")
+ math.max(y, 0.1)
--- End diff --
I have not seen a formal justification for the choice of 0.1 in R. This
seminal
[paper](http://users.du.se/~lrn/StatMod10/HomeExercise2/Nelder_Pregibon.pdf)
suggests 1/6 (about 0.17) to be the best constant. I would prefer to be
consistent with R so that we can make comparison. Using a constant is a good
idea.
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